I'm passionate about transforming data into actionable insights that drive strategic decisions and measurable outcomes. Passionate about data storytelling, AI automation, and solving business problems using large language models, dashboards, and ETL workflows. With a strong foundation in both data analytics and business understanding, I specialize in uncovering trends, solving real-world problems, and helping organizations make data-backed decisions.
I enjoy working with large datasets, building dashboards, and generating reports that speak the language of business. From cleaning raw data to visualizing key metrics, I make sure every data point counts.
Python – Data manipulation (Pandas, NumPy), analysis, automation, LLM integration (Gemini Pro, OpenAI), scripting
SQL – Advanced querying, joins, CTEs, window functions, optimization, window functions, data validation
Excel – Functions, pivot tables, dashboards, and VBA basics
Power BI – Interactive dashboards, KPIs and data storytelling
Tableau – Dynamic reports and visual analytics
Matplotlib / Seaborn / Plotly / Streamlit – Custom visuals, user-interactive web dashboards
ETL Processes – Cleaning, transforming, and loading structured data
PIs & Web Scraping – Requests, BeautifulSoup
Git & GitHub – Version control and collaborative development
Jupyter Notebook / Google Colab – Exploratory data analysis notebooks
LLMs & GenAI – Google Gemini, OpenAI GPT, RAG-style prompting
Prompt Engineering – Structured JSON output, task chaining
NLP & NLG – Resume matching, cover letter generation, summarization
ETL Pipelines – Data extraction, transformation, loading via Python/SQL
APIs & Web Scraping – Requests, BeautifulSoup, Gemini API, OpenAI API
Version Control – Git, GitHub
Notebooks – Jupyter, Google Colab
Here are a few projects that reflect my skills and problem-solving capabilities:
AI agent that tailors resumes, matches job descriptions, and writes personalized cover letters.
- Tools: Python, Google Gemini Pro, Prompt Engineering
- Outputs: Match scoring, bullet suggestions, JSON-structured output
- Featured on Kaggle, GitHub, and YouTube
🔗 GitHub Repo | Kaggle Notebook | YouTube Demo
Leverages LLMs and AI agents to automatically analyze reports (PDF/Excel/CSV) and generate actionable summaries, charts, and insights.
🔍 Automated insight extraction using Python & OpenAI APIs
📊 Visualizations using Plotly and Matplotlib
🤖 Intelligent summarization & natural language generation
An interactive Streamlit application visualizing and comparing cost of living indices across various countries.
Technologies Used: Python, Streamlit, Pandas, Plotly, Seaborn
Features:
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🗺️ Compare indices by country using visual charts
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📊 Built with Plotly, Seaborn, Streamlit
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🧮 Focus on rent, groceries, utilities, etc.
Outcome: Facilitates users in making informed decisions regarding global cost comparisons.
Analyzes sales data and builds time-series models to forecast future trends.
- 🧼 Data wrangling and preprocessing with Pandas
- 📈 Time-series forecasting with ARIMA & statsmodels
- 📉 Actionable sales insights for business planning
📬 Let’s Connect
I’m always excited to collaborate, learn, or just chat about data!
📧 Email: [email protected]
🧠 Portfolio Website: https://sreejabethu.github.io/
📍 Location: United States (Open to Remote & Hybrid Roles)
Let’s make data work smarter with AI 🚀